Dashboard

Row

Total Coronavirus Cases in Egypt

1794

Total Coronavirus Deaths in Egypt

135

Total Coronavirus Recovered Cases in Egypt

384

Cases which had an outcome
Deaths/Discharged : 135 (26%)
Recovered/Discharged : 384 (74%)

Closed Cases: 519

Currently Infected Patients

Active Cases: 1275

Row

Confirmed Cases per day

Deaths per day

Recovered Cases per day

Row

Total Confirmed Cases

Total Deaths

Total Recovered


  1. https://github.com/Sherif-Embarak/

---
title: "Covid-19 in Egypt"
date:  "Last update: `r Sys.time()`"
author: Sherif Embarak^[https://github.com/Sherif-Embarak/]
output:
  flexdashboard::flex_dashboard:
    theme: lumen
    social: menu
    source: embed
    vertical_layout: scroll
    orientation: rows
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
rm(list=ls(all=TRUE))
options(stringsAsFactors = FALSE)
library(ggplot2)
library(plotly)
library(flexdashboard)
library(DT)
library(plotly)
library(knitr)
library(lubridate)
library(crosstalk)

setwd("D:/work/git corona/")
df <- read.csv("eg_covid.csv")
df$Day <- mdy(df$Day)
df$Day <- paste(day(df$Day) , months.Date(df$Day) )
df$Curfew <- as.character(df$Curfew)
df <- df[,1:8]
total_cases <- df$Total.Cases[nrow(df)]
total_deaths <- df$Total.Deaths[nrow(df)]
total_recovered <- df$Total.Recovered[nrow(df)]
closed <- total_deaths+total_recovered
active <- total_cases - closed
library(crosstalk)
df$Day <- factor(df$Day, levels = df$Day)
xlabel <- df$Day[as.integer(seq(1 , nrow(df) , length.out = 10))]
hk <- highlight_key(df, ~Total.Cases)

chart1 <-ggplotly(ggplot(hk, aes(x=Day, y=New.Cases, fill=Curfew)) + scale_x_discrete(breaks = xlabel)+
  geom_bar(width = 0.3, stat = "identity")+scale_fill_manual(values = c("#6698FF", "#153E7E"))+
  theme(panel.grid.major.x  = element_blank(), axis.text.x = element_text(angle = 70, hjust = 1)),tooltip = c("x", "y")) %>%
       highlight(off = "plotly_relayout")

chart2 <-ggplotly(ggplot(hk, aes(x=Day, y=New.Deaths, fill=Curfew)) + scale_x_discrete(breaks = xlabel)+
  geom_bar(width = 0.3, stat = "identity")+scale_fill_manual(values = c("#6698FF", "#153E7E"))+
  theme(panel.grid.major.x  = element_blank(), axis.text.x = element_text(angle = 70, hjust = 1)),tooltip = c("x", "y")) %>%
       highlight(off = "plotly_relayout")

chart3 <-ggplotly(ggplot(hk, aes(x=Day, y=New.Recovered, fill=Curfew)) + scale_x_discrete(breaks = xlabel)+
  geom_bar(width = 0.3, stat = "identity")+scale_fill_manual(values = c("#6698FF", "#153E7E"))+
  theme(panel.grid.major.x  = element_blank(), axis.text.x = element_text(angle = 70, hjust = 1)),tooltip = c("x", "y")) %>%
       highlight(off = "plotly_relayout")

chart4 <- ggplotly(ggplot(data=hk, aes(x=Day, y=Total.Cases, group=1))+ scale_x_discrete(breaks = xlabel)+
 geom_line(color="#33CCFF", size=1)+theme(panel.grid.major.x  = element_blank(), axis.text.x = element_text(angle = 70, hjust = 1))+
  geom_point(color="#33CCFF"),tooltip = c("x", "y")) %>%
       highlight(off = "plotly_relayout")

chart5 <- ggplotly(ggplot(data=hk, aes(x=Day, y=Total.Deaths, group=1))+ scale_x_discrete(breaks = xlabel)+
 geom_line(color="#FF9900", size=1)+theme(panel.grid.major.x  = element_blank(), axis.text.x = element_text(angle = 70, hjust = 1))+
  geom_point(color="#FF9900"),tooltip = c("x", "y")) %>%
       highlight(off = "plotly_relayout")

chart6 <- ggplotly(ggplot(data=hk, aes(x=Day, y=Total.Recovered, group=1))+ scale_x_discrete(breaks = xlabel)+
 geom_line(color="#00DDDD", size=1)+theme(panel.grid.major.x  = element_blank(), axis.text.x = element_text(angle = 70, hjust = 1))+
  geom_point(color="#00DDDD"),tooltip = c("x", "y"))%>%
       highlight(off = "plotly_relayout")


```

Dashboard
=======================================================================

Row
-----------------------------------------------------------------------

### Total Coronavirus Cases in Egypt

```{r, echo=FALSE}
valueBox(total_cases)
```

### Total Coronavirus Deaths in Egypt 

```{r, echo=FALSE}
valueBox(total_deaths, color="warning")
```

### Total Coronavirus Recovered Cases in Egypt

```{r, echo=FALSE}
valueBox(total_recovered , color = "#00DDDD")
```

### Cases which had an outcome `r "
"` `r paste0("Deaths/Discharged : ", total_deaths, " (", round((total_deaths/closed)*100,1),"%)" )` `r "
"` `r paste0("Recovered/Discharged : ", total_recovered, " (", round((total_recovered/closed)*100,1),"%)" )` ```{r, echo=FALSE} valueBox(paste("Closed Cases: ",closed)) ``` ### Currently Infected Patients ```{r, echo=FALSE} valueBox(paste("Active Cases: ",active)) ``` Row ------------------------------------- ### Confirmed Cases per day ```{r, echo=FALSE ,fig.height=3} chart1 ``` ### Deaths per day ```{r, echo=FALSE ,fig.height=3} chart2 ``` ### Recovered Cases per day ```{r, echo=FALSE ,fig.height=3} chart3 ``` Row ------------------------------------- ### Total Confirmed Cases ```{r, echo=FALSE, warning=FALSE,message=FALSE,results='asis',fig.show='asis'} chart4 ``` ### Total Deaths ```{r, echo=FALSE, warning=FALSE,message=FALSE,results='asis',fig.show='asis'} chart5 ``` ### Total Recovered ```{r, echo=FALSE, warning=FALSE,message=FALSE,results='asis',fig.show='asis'} chart6 ``` Column {.sidebar data-width=350} ------------------------------------- ### Distibution of Cases This dashboard has been created according to worldometers.info design. In order to compensate with the lack of real time statistical data in Egypt, the given data below will be updated daily at 10:00 PM (Cairo Time).
Stay Home, Stay Safe.

```{r, echo=FALSE } DT::datatable(hk,class = 'cell-border stripe hover compact', rownames = FALSE , options = list(pageLength = 10,order = list(2, 'desc')))%>% formatStyle('New.Cases', backgroundColor = '#FFEEAA') %>% formatStyle('New.Deaths',backgroundColor = 'red')%>% formatStyle(names(df),fontWeight = 'bold')%>% formatStyle('Curfew', backgroundColor = styleEqual(c(0, 1), c('#a6cee3', '#1f78b4')))%>% highlight(on = "plotly_click" , off ="plotly_doubleclick") ```